Swedroe: When False Factors Are Exposed

June 20, 2016

The world of finance and asset pricing used to be fairly simple. At first, there was just the single-factor capital asset pricing model, with market risk (beta) as the sole factor to explain the differences in returns of diversified portfolios. Over time, the working model evolved into a still relatively simple four-factor model, adding value, size and momentum. Each of these four factors carried large premiums.

However, as John Cochrane put it, today we have a literal factor zoo, with more than 600 factors having been identified in the literature (roughly 300 of which have been identified in top journal articles and highly regarded working papers).

Subsequent research has found that in out-of-sample tests, about half the factors produced zero to negative premia, even prior to considering transaction costs. Thus, the findings involving these factors were likely the result of data mining, or they were just lucky outcomes. Either that or they were behavioral anomalies that, post-publication, would be easily arbitraged away.

The Effect Of Publication

In the study “Does Academic Research Destroy Stock Return Predictability?”, published in the January 2016 issue of the Journal of Finance, authors R. David McLean and Jeffrey Pontiff re-examined 82 factors published in tier-one academic journals and were only able to replicate the reported results for 72 of them. At least 10 out of 82 factors were artifacts of reporting mistakes in the databases, which have since been corrected.

They also found that, post-publication, the “average characteristic’s return decays by about 35%.” In addition, they found that “characteristic portfolios that consist more of stocks that are costly to arbitrage decline less post-publication. This is consistent with the idea that arbitrage costs limit arbitrage and protect mispricing.”

Paul Calluzzo, Fabio Moneta and Selim Topaloglu contribute to the literature and to our understanding of how markets work and become more efficient over time (the adaptive markets hypothesis) with their December 2015 study, “Anomalies are Publicized Broadly, Institutions Trade Accordingly, and Returns Decay Correspondingly.”

They hypothesized: “Institutions can act as arbitrageurs and correct anomaly mispricing, but they need to know about the anomaly and have the incentives to act on the information to fulfill this role.” To test their assumption, the authors considered whether “knowledge of the anomaly is in the public domain based on the year of academic publication” and if “the accounting data necessary to compute the anomaly rankings is publicly available.”

They then studied the trading behavior of institutional investors in 14 well-documented anomalies, building long-short portfolios to determine whether they exploited the anomalies and helped bring equity prices closer to efficient levels. The 14 anomalies they evaluated were: total accruals, net stock issues, composite equity issues, net operating assets, gross profitability, asset growth, capital investments, investment-to-assets, book-to-market, momentum, distress (failure probability), Ohlson O-score, return on assets and post-earnings announcement drift.

Anomaly Study Results

Their study covered the period January 1982 through June 2014. Following is a summary of their findings:


Find your next ETF

Reset All